from sklearn_benchmarks.report import Reporting
import pandas as pd
pd.set_option('display.max_colwidth', None)
pd.set_option('display.max_columns', None)
pd.set_option('display.max_rows', None)
reporting = Reporting(config_file_path="config.yml")
reporting.run()
| hour | min | sec | |
|---|---|---|---|
| algo | |||
| KNeighborsClassifier | 0.0 | 13.0 | 40.302472 |
| daal4py_KNeighborsClassifier | 0.0 | 5.0 | 16.969540 |
| KNeighborsClassifier_kd_tree | 0.0 | 6.0 | 39.341896 |
| daal4py_KNeighborsClassifier_kd_tree | 0.0 | 1.0 | 50.069258 |
| KMeans_tall | 0.0 | 1.0 | 47.681629 |
| daal4py_KMeans_tall | 0.0 | 1.0 | 18.703511 |
| KMeans_short | 0.0 | 0.0 | 25.815144 |
| daal4py_KMeans_short | 0.0 | 0.0 | 12.654353 |
| LogisticRegression | 0.0 | 1.0 | 7.733477 |
| daal4py_LogisticRegression | 0.0 | 1.0 | 1.248076 |
| Ridge | 0.0 | 0.0 | 1.095413 |
| daal4py_Ridge | 0.0 | 0.0 | 0.830633 |
| total | 0.0 | 33.0 | 22.534776 |
| estimator | function | mean_sklearn | stdev_sklearn | n_samples_train | n_samples | n_features | algorithm | n_jobs | n_neighbors | accuracy_score_sklearn | accuracy_score_daal4py | mean_daal4py | stdev_daal4py | speedup | stdev_speedup | profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KNeighborsClassifier | fit | 0.147 | 0.003 | 1000000 | 1000000 | 100 | brute | -1 | 1 | NaN | NaN | 0.495 | 0.005 | 0.297 | 0.000 | See |
| 1 | KNeighborsClassifier | predict | 0.197 | 0.017 | 1000000 | 1 | 100 | brute | -1 | 1 | 1.0 | 1.0 | 0.112 | 0.008 | 1.749 | 0.012 | See |
| 2 | KNeighborsClassifier | predict | 30.543 | 0.000 | 1000000 | 1000 | 100 | brute | -1 | 1 | 1.0 | 1.0 | 3.855 | 0.028 | 7.923 | 0.000 | See |
| 3 | KNeighborsClassifier | fit | 0.143 | 0.003 | 1000000 | 1000000 | 100 | brute | -1 | 5 | NaN | NaN | 0.500 | 0.014 | 0.285 | 0.001 | See |
| 4 | KNeighborsClassifier | predict | 0.190 | 0.011 | 1000000 | 1 | 100 | brute | -1 | 5 | 1.0 | 1.0 | 0.115 | 0.005 | 1.651 | 0.005 | See |
| 5 | KNeighborsClassifier | predict | 38.888 | 0.000 | 1000000 | 1000 | 100 | brute | -1 | 5 | 1.0 | 1.0 | 3.909 | 0.035 | 9.949 | 0.000 | See |
| 6 | KNeighborsClassifier | fit | 0.137 | 0.003 | 1000000 | 1000000 | 100 | brute | -1 | 100 | NaN | NaN | 0.500 | 0.011 | 0.274 | 0.001 | See |
| 7 | KNeighborsClassifier | predict | 0.220 | 0.015 | 1000000 | 1 | 100 | brute | -1 | 100 | 1.0 | 1.0 | 0.107 | 0.005 | 2.048 | 0.007 | See |
| 8 | KNeighborsClassifier | predict | 38.635 | 0.000 | 1000000 | 1000 | 100 | brute | -1 | 100 | 1.0 | 1.0 | 3.988 | 0.046 | 9.688 | 0.000 | See |
| 9 | KNeighborsClassifier | fit | 0.135 | 0.003 | 1000000 | 1000000 | 100 | brute | 1 | 1 | NaN | NaN | 0.503 | 0.008 | 0.268 | 0.001 | See |
| 10 | KNeighborsClassifier | predict | 0.219 | 0.054 | 1000000 | 1 | 100 | brute | 1 | 1 | 1.0 | 1.0 | 0.112 | 0.009 | 1.954 | 0.067 | See |
| 11 | KNeighborsClassifier | predict | 15.811 | 0.118 | 1000000 | 1000 | 100 | brute | 1 | 1 | 1.0 | 1.0 | 3.834 | 0.023 | 4.124 | 0.000 | See |
| 12 | KNeighborsClassifier | fit | 0.131 | 0.003 | 1000000 | 1000000 | 100 | brute | 1 | 5 | NaN | NaN | 0.495 | 0.005 | 0.266 | 0.001 | See |
| 13 | KNeighborsClassifier | predict | 0.202 | 0.003 | 1000000 | 1 | 100 | brute | 1 | 5 | 1.0 | 1.0 | 0.103 | 0.003 | 1.963 | 0.001 | See |
| 14 | KNeighborsClassifier | predict | 24.810 | 0.116 | 1000000 | 1000 | 100 | brute | 1 | 5 | 1.0 | 1.0 | 3.855 | 0.049 | 6.436 | 0.000 | See |
| 15 | KNeighborsClassifier | fit | 0.143 | 0.005 | 1000000 | 1000000 | 100 | brute | 1 | 100 | NaN | NaN | 0.496 | 0.009 | 0.289 | 0.001 | See |
| 16 | KNeighborsClassifier | predict | 0.206 | 0.003 | 1000000 | 1 | 100 | brute | 1 | 100 | 1.0 | 1.0 | 0.102 | 0.001 | 2.011 | 0.000 | See |
| 17 | KNeighborsClassifier | predict | 24.407 | 0.018 | 1000000 | 1000 | 100 | brute | 1 | 100 | 1.0 | 1.0 | 3.910 | 0.058 | 6.242 | 0.000 | See |
| 18 | KNeighborsClassifier | fit | 0.058 | 0.001 | 1000000 | 1000000 | 2 | brute | -1 | 1 | NaN | NaN | 0.106 | 0.005 | 0.545 | 0.002 | See |
| 19 | KNeighborsClassifier | predict | 0.021 | 0.002 | 1000000 | 1 | 2 | brute | -1 | 1 | 1.0 | 0.0 | 0.004 | 0.000 | 4.871 | 0.013 | See |
| 20 | KNeighborsClassifier | predict | 24.378 | 0.048 | 1000000 | 1000 | 2 | brute | -1 | 1 | 1.0 | 0.0 | 0.818 | 0.016 | 29.798 | 0.000 | See |
| 21 | KNeighborsClassifier | fit | 0.057 | 0.001 | 1000000 | 1000000 | 2 | brute | -1 | 5 | NaN | NaN | 0.098 | 0.003 | 0.580 | 0.002 | See |
| 22 | KNeighborsClassifier | predict | 0.031 | 0.001 | 1000000 | 1 | 2 | brute | -1 | 5 | 1.0 | 1.0 | 0.004 | 0.000 | 7.283 | 0.012 | See |
| 23 | KNeighborsClassifier | predict | 32.901 | 0.000 | 1000000 | 1000 | 2 | brute | -1 | 5 | 1.0 | 1.0 | 0.823 | 0.016 | 39.973 | 0.000 | See |
| 24 | KNeighborsClassifier | fit | 0.059 | 0.002 | 1000000 | 1000000 | 2 | brute | -1 | 100 | NaN | NaN | 0.105 | 0.006 | 0.562 | 0.004 | See |
| 25 | KNeighborsClassifier | predict | 0.033 | 0.002 | 1000000 | 1 | 2 | brute | -1 | 100 | 1.0 | 1.0 | 0.004 | 0.000 | 7.327 | 0.009 | See |
| 26 | KNeighborsClassifier | predict | 32.547 | 0.000 | 1000000 | 1000 | 2 | brute | -1 | 100 | 1.0 | 1.0 | 0.889 | 0.023 | 36.597 | 0.001 | See |
| 27 | KNeighborsClassifier | fit | 0.058 | 0.001 | 1000000 | 1000000 | 2 | brute | 1 | 1 | NaN | NaN | 0.114 | 0.006 | 0.510 | 0.003 | See |
| 28 | KNeighborsClassifier | predict | 0.016 | 0.001 | 1000000 | 1 | 2 | brute | 1 | 1 | 1.0 | 0.0 | 0.005 | 0.000 | 3.417 | 0.008 | See |
| 29 | KNeighborsClassifier | predict | 10.926 | 0.050 | 1000000 | 1000 | 2 | brute | 1 | 1 | 1.0 | 0.0 | 0.885 | 0.157 | 12.342 | 0.031 | See |
| 30 | KNeighborsClassifier | fit | 0.059 | 0.001 | 1000000 | 1000000 | 2 | brute | 1 | 5 | NaN | NaN | 0.106 | 0.002 | 0.560 | 0.001 | See |
| 31 | KNeighborsClassifier | predict | 0.028 | 0.003 | 1000000 | 1 | 2 | brute | 1 | 5 | 1.0 | 1.0 | 0.005 | 0.000 | 6.072 | 0.015 | See |
| 32 | KNeighborsClassifier | predict | 19.154 | 0.075 | 1000000 | 1000 | 2 | brute | 1 | 5 | 1.0 | 1.0 | 0.815 | 0.008 | 23.510 | 0.000 | See |
| 33 | KNeighborsClassifier | fit | 0.056 | 0.001 | 1000000 | 1000000 | 2 | brute | 1 | 100 | NaN | NaN | 0.106 | 0.001 | 0.527 | 0.001 | See |
| 34 | KNeighborsClassifier | predict | 0.027 | 0.002 | 1000000 | 1 | 2 | brute | 1 | 100 | 1.0 | 1.0 | 0.005 | 0.001 | 5.922 | 0.020 | See |
| 35 | KNeighborsClassifier | predict | 19.395 | 0.202 | 1000000 | 1000 | 2 | brute | 1 | 100 | 1.0 | 1.0 | 0.891 | 0.011 | 21.770 | 0.000 | See |
Shared hyperparameters:
| value | |
|---|---|
| algorithm | brute |
| estimator | function | mean_sklearn | stdev_sklearn | n_samples_train | n_samples | n_features | algorithm | n_jobs | n_neighbors | accuracy_score_sklearn | accuracy_score_daal4py | mean_daal4py | stdev_daal4py | speedup | stdev_speedup | profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KNeighborsClassifier_kd_tree | fit | 2.900 | 0.075 | 1000000 | 1000000 | 10 | kd_tree | -1 | 1 | NaN | NaN | 0.736 | 0.013 | 3.940 | 0.001 | See |
| 1 | KNeighborsClassifier_kd_tree | predict | 0.003 | 0.000 | 1000000 | 1 | 10 | kd_tree | -1 | 1 | 1.0 | 1.0 | 0.001 | 0.000 | 4.579 | 0.154 | See |
| 2 | KNeighborsClassifier_kd_tree | predict | 0.475 | 0.020 | 1000000 | 1000 | 10 | kd_tree | -1 | 1 | 1.0 | 1.0 | 0.127 | 0.002 | 3.738 | 0.002 | See |
| 3 | KNeighborsClassifier_kd_tree | fit | 2.819 | 0.047 | 1000000 | 1000000 | 10 | kd_tree | -1 | 5 | NaN | NaN | 0.785 | 0.026 | 3.592 | 0.001 | See |
| 4 | KNeighborsClassifier_kd_tree | predict | 0.003 | 0.000 | 1000000 | 1 | 10 | kd_tree | -1 | 5 | 1.0 | 1.0 | 0.001 | 0.000 | 3.770 | 0.134 | See |
| 5 | KNeighborsClassifier_kd_tree | predict | 0.860 | 0.011 | 1000000 | 1000 | 10 | kd_tree | -1 | 5 | 1.0 | 1.0 | 0.228 | 0.006 | 3.777 | 0.001 | See |
| 6 | KNeighborsClassifier_kd_tree | fit | 2.707 | 0.063 | 1000000 | 1000000 | 10 | kd_tree | -1 | 100 | NaN | NaN | 0.752 | 0.020 | 3.600 | 0.001 | See |
| 7 | KNeighborsClassifier_kd_tree | predict | 0.004 | 0.001 | 1000000 | 1 | 10 | kd_tree | -1 | 100 | 1.0 | 1.0 | 0.001 | 0.000 | 3.956 | 0.148 | See |
| 8 | KNeighborsClassifier_kd_tree | predict | 2.798 | 0.016 | 1000000 | 1000 | 10 | kd_tree | -1 | 100 | 1.0 | 1.0 | 0.699 | 0.012 | 4.005 | 0.000 | See |
| 9 | KNeighborsClassifier_kd_tree | fit | 2.764 | 0.042 | 1000000 | 1000000 | 10 | kd_tree | 1 | 1 | NaN | NaN | 0.775 | 0.015 | 3.565 | 0.001 | See |
| 10 | KNeighborsClassifier_kd_tree | predict | 0.001 | 0.000 | 1000000 | 1 | 10 | kd_tree | 1 | 1 | 1.0 | 1.0 | 0.001 | 0.000 | 1.501 | 0.185 | See |
| 11 | KNeighborsClassifier_kd_tree | predict | 0.758 | 0.011 | 1000000 | 1000 | 10 | kd_tree | 1 | 1 | 1.0 | 1.0 | 0.123 | 0.004 | 6.172 | 0.001 | See |
| 12 | KNeighborsClassifier_kd_tree | fit | 2.695 | 0.083 | 1000000 | 1000000 | 10 | kd_tree | 1 | 5 | NaN | NaN | 0.752 | 0.020 | 3.586 | 0.002 | See |
| 13 | KNeighborsClassifier_kd_tree | predict | 0.001 | 0.001 | 1000000 | 1 | 10 | kd_tree | 1 | 5 | 1.0 | 1.0 | 0.001 | 0.000 | 1.460 | 0.502 | See |
| 14 | KNeighborsClassifier_kd_tree | predict | 1.420 | 0.036 | 1000000 | 1000 | 10 | kd_tree | 1 | 5 | 1.0 | 1.0 | 0.231 | 0.007 | 6.140 | 0.001 | See |
| 15 | KNeighborsClassifier_kd_tree | fit | 3.005 | 0.121 | 1000000 | 1000000 | 10 | kd_tree | 1 | 100 | NaN | NaN | 0.790 | 0.012 | 3.806 | 0.002 | See |
| 16 | KNeighborsClassifier_kd_tree | predict | 0.003 | 0.001 | 1000000 | 1 | 10 | kd_tree | 1 | 100 | 1.0 | 1.0 | 0.001 | 0.000 | 2.373 | 0.212 | See |
| 17 | KNeighborsClassifier_kd_tree | predict | 5.069 | 0.069 | 1000000 | 1000 | 10 | kd_tree | 1 | 100 | 1.0 | 1.0 | 0.697 | 0.015 | 7.276 | 0.001 | See |
| 18 | KNeighborsClassifier_kd_tree | fit | 1.493 | 0.037 | 1000000 | 1000000 | 2 | kd_tree | -1 | 1 | NaN | NaN | 0.514 | 0.017 | 2.903 | 0.002 | See |
| 19 | KNeighborsClassifier_kd_tree | predict | 0.003 | 0.000 | 1000000 | 1 | 2 | kd_tree | -1 | 1 | 1.0 | 1.0 | 0.000 | 0.000 | 16.649 | 0.223 | See |
| 20 | KNeighborsClassifier_kd_tree | predict | 0.040 | 0.002 | 1000000 | 1000 | 2 | kd_tree | -1 | 1 | 1.0 | 1.0 | 0.001 | 0.000 | 45.458 | 0.084 | See |
| 21 | KNeighborsClassifier_kd_tree | fit | 1.494 | 0.039 | 1000000 | 1000000 | 2 | kd_tree | -1 | 5 | NaN | NaN | 0.515 | 0.011 | 2.898 | 0.001 | See |
| 22 | KNeighborsClassifier_kd_tree | predict | 0.002 | 0.000 | 1000000 | 1 | 2 | kd_tree | -1 | 5 | 1.0 | 1.0 | 0.000 | 0.000 | 14.978 | 0.239 | See |
| 23 | KNeighborsClassifier_kd_tree | predict | 0.042 | 0.002 | 1000000 | 1000 | 2 | kd_tree | -1 | 5 | 1.0 | 1.0 | 0.001 | 0.000 | 35.321 | 0.060 | See |
| 24 | KNeighborsClassifier_kd_tree | fit | 1.488 | 0.033 | 1000000 | 1000000 | 2 | kd_tree | -1 | 100 | NaN | NaN | 0.506 | 0.016 | 2.938 | 0.001 | See |
| 25 | KNeighborsClassifier_kd_tree | predict | 0.003 | 0.001 | 1000000 | 1 | 2 | kd_tree | -1 | 100 | 1.0 | 1.0 | 0.000 | 0.000 | 16.566 | 0.278 | See |
| 26 | KNeighborsClassifier_kd_tree | predict | 0.066 | 0.011 | 1000000 | 1000 | 2 | kd_tree | -1 | 100 | 1.0 | 1.0 | 0.008 | 0.001 | 8.517 | 0.036 | See |
| 27 | KNeighborsClassifier_kd_tree | fit | 1.472 | 0.028 | 1000000 | 1000000 | 2 | kd_tree | 1 | 1 | NaN | NaN | 0.536 | 0.015 | 2.745 | 0.001 | See |
| 28 | KNeighborsClassifier_kd_tree | predict | 0.001 | 0.000 | 1000000 | 1 | 2 | kd_tree | 1 | 1 | 1.0 | 1.0 | 0.000 | 0.000 | 5.268 | 0.274 | See |
| 29 | KNeighborsClassifier_kd_tree | predict | 0.038 | 0.001 | 1000000 | 1000 | 2 | kd_tree | 1 | 1 | 1.0 | 1.0 | 0.001 | 0.000 | 46.608 | 0.072 | See |
| 30 | KNeighborsClassifier_kd_tree | fit | 1.471 | 0.028 | 1000000 | 1000000 | 2 | kd_tree | 1 | 5 | NaN | NaN | 0.520 | 0.008 | 2.827 | 0.001 | See |
| 31 | KNeighborsClassifier_kd_tree | predict | 0.001 | 0.001 | 1000000 | 1 | 2 | kd_tree | 1 | 5 | 1.0 | 1.0 | 0.000 | 0.000 | 5.699 | 0.630 | See |
| 32 | KNeighborsClassifier_kd_tree | predict | 0.042 | 0.001 | 1000000 | 1000 | 2 | kd_tree | 1 | 5 | 1.0 | 1.0 | 0.001 | 0.000 | 34.851 | 0.052 | See |
| 33 | KNeighborsClassifier_kd_tree | fit | 1.481 | 0.028 | 1000000 | 1000000 | 2 | kd_tree | 1 | 100 | NaN | NaN | 0.525 | 0.009 | 2.819 | 0.001 | See |
| 34 | KNeighborsClassifier_kd_tree | predict | 0.010 | 0.027 | 1000000 | 1 | 2 | kd_tree | 1 | 100 | 1.0 | 1.0 | 0.000 | 0.000 | 53.170 | 7.547 | See |
| 35 | KNeighborsClassifier_kd_tree | predict | 0.073 | 0.001 | 1000000 | 1000 | 2 | kd_tree | 1 | 100 | 1.0 | 1.0 | 0.009 | 0.001 | 8.432 | 0.005 | See |
Shared hyperparameters:
| value | |
|---|---|
| algorithm | kd_tree |
| estimator | function | mean_sklearn | stdev_sklearn | n_samples_train | n_samples | n_features | algorithm | init | max_iter | n_clusters | n_init | tol | n_iter_sklearn | adjusted_rand_score_sklearn | n_iter_daal4py | adjusted_rand_score_daal4py | mean_daal4py | stdev_daal4py | speedup | stdev_speedup | profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KMeans_tall | fit | 0.658 | 0.014 | 1000000 | 1000000 | 2 | full | k-means++ | 30 | 3 | 1 | 0.0 | 30.0 | NaN | 30.0 | NaN | 0.326 | 0.008 | 2.019 | 0.001 | See |
| 1 | KMeans_tall | predict | 0.000 | 0.000 | 1000000 | 1 | 2 | full | k-means++ | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 2.139 | 0.319 | See |
| 2 | KMeans_tall | predict | 0.000 | 0.000 | 1000000 | 1000 | 2 | full | k-means++ | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 1.891 | 0.232 | See |
| 3 | KMeans_tall | fit | 0.545 | 0.006 | 1000000 | 1000000 | 2 | full | random | 30 | 3 | 1 | 0.0 | 30.0 | NaN | 30.0 | NaN | 0.294 | 0.012 | 1.856 | 0.002 | See |
| 4 | KMeans_tall | predict | 0.000 | 0.000 | 1000000 | 1 | 2 | full | random | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 1.911 | 0.260 | See |
| 5 | KMeans_tall | predict | 0.000 | 0.000 | 1000000 | 1000 | 2 | full | random | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 1.923 | 0.259 | See |
| 6 | KMeans_tall | fit | 7.408 | 0.090 | 1000000 | 1000000 | 100 | full | k-means++ | 30 | 3 | 1 | 0.0 | 30.0 | NaN | 30.0 | NaN | 4.014 | 0.052 | 1.845 | 0.000 | See |
| 7 | KMeans_tall | predict | 0.000 | 0.000 | 1000000 | 1 | 100 | full | k-means++ | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 2.015 | 0.269 | See |
| 8 | KMeans_tall | predict | 0.001 | 0.000 | 1000000 | 1000 | 100 | full | k-means++ | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 2.034 | 0.192 | See |
| 9 | KMeans_tall | fit | 6.667 | 0.112 | 1000000 | 1000000 | 100 | full | random | 30 | 3 | 1 | 0.0 | 30.0 | NaN | 30.0 | NaN | 3.801 | 0.046 | 1.754 | 0.000 | See |
| 10 | KMeans_tall | predict | 0.000 | 0.000 | 1000000 | 1 | 100 | full | random | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 1.712 | 0.202 | See |
| 11 | KMeans_tall | predict | 0.001 | 0.001 | 1000000 | 1000 | 100 | full | random | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 3.856 | 1.238 | See |
Shared hyperparameters:
| value | |
|---|---|
| algorithm | full |
| n_clusters | 3 |
| max_iter | 30 |
| n_init | 1 |
| tol | 0.0 |
| estimator | function | mean_sklearn | stdev_sklearn | n_samples_train | n_samples | n_features | algorithm | init | max_iter | n_clusters | n_init | tol | n_iter_sklearn | adjusted_rand_score_sklearn | n_iter_daal4py | adjusted_rand_score_daal4py | mean_daal4py | stdev_daal4py | speedup | stdev_speedup | profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KMeans_short | fit | 0.387 | 0.016 | 10000 | 10000 | 2 | full | k-means++ | 30 | 300 | 1 | 0.0 | 30.0 | NaN | 28.0 | NaN | 0.147 | 0.007 | 2.641 | 0.004 | See |
| 1 | KMeans_short | predict | 0.000 | 0.000 | 10000 | 1 | 2 | full | k-means++ | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 2.200 | 0.317 | See |
| 2 | KMeans_short | predict | 0.001 | 0.000 | 10000 | 1000 | 2 | full | k-means++ | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.001 | 0.000 | 1.278 | 0.052 | See |
| 3 | KMeans_short | fit | 0.142 | 0.004 | 10000 | 10000 | 2 | full | random | 30 | 300 | 1 | 0.0 | 30.0 | NaN | 30.0 | NaN | 0.068 | 0.001 | 2.084 | 0.001 | See |
| 4 | KMeans_short | predict | 0.000 | 0.000 | 10000 | 1 | 2 | full | random | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 2.161 | 0.279 | See |
| 5 | KMeans_short | predict | 0.001 | 0.000 | 10000 | 1000 | 2 | full | random | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.001 | 0.000 | 1.379 | 0.066 | See |
| 6 | KMeans_short | fit | 1.233 | 0.028 | 10000 | 10000 | 100 | full | k-means++ | 30 | 300 | 1 | 0.0 | 18.0 | NaN | 17.0 | NaN | 0.579 | 0.022 | 2.130 | 0.002 | See |
| 7 | KMeans_short | predict | 0.001 | 0.000 | 10000 | 1 | 100 | full | k-means++ | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 1.986 | 0.444 | See |
| 8 | KMeans_short | predict | 0.006 | 0.003 | 10000 | 1000 | 100 | full | k-means++ | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.001 | 0.000 | 4.284 | 0.212 | See |
| 9 | KMeans_short | fit | 0.372 | 0.041 | 10000 | 10000 | 100 | full | random | 30 | 300 | 1 | 0.0 | 30.0 | NaN | 30.0 | NaN | 0.297 | 0.035 | 1.251 | 0.026 | See |
| 10 | KMeans_short | predict | 0.000 | 0.000 | 10000 | 1 | 100 | full | random | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 2.045 | 0.203 | See |
| 11 | KMeans_short | predict | 0.008 | 0.001 | 10000 | 1000 | 100 | full | random | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.002 | 0.000 | 5.562 | 0.040 | See |
Shared hyperparameters:
| value | |
|---|---|
| algorithm | full |
| n_clusters | 300 |
| max_iter | 30 |
| n_init | 1 |
| tol | 0.0 |
| estimator | function | mean_sklearn | stdev_sklearn | n_samples_train | n_samples | n_features | C | class_weight | dual | fit_intercept | intercept_scaling | l1_ratio | max_iter | multi_class | n_jobs | penalty | random_state | solver | tol | verbose | warm_start | n_iter | mean_daal4py | stdev_daal4py | speedup | stdev_speedup | profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | LogisticRegression | fit | 15.331 | 0.036 | 1000000 | 1000000 | 100 | 1.0 | NaN | False | True | 1 | NaN | 100 | auto | NaN | l2 | NaN | lbfgs | 0.0 | 0 | False | [20] | 15.709 | 0.083 | 0.976 | 0.000 | See |
| 1 | LogisticRegression | predict | 0.000 | 0.000 | 1000000 | 1 | 100 | 1.0 | NaN | False | True | 1 | NaN | 100 | auto | NaN | l2 | NaN | lbfgs | 0.0 | 0 | False | NaN | 0.000 | 0.000 | 0.396 | 1.107 | See |
| 2 | LogisticRegression | predict | 0.000 | 0.000 | 1000000 | 1000 | 100 | 1.0 | NaN | False | True | 1 | NaN | 100 | auto | NaN | l2 | NaN | lbfgs | 0.0 | 0 | False | NaN | 0.000 | 0.000 | 0.840 | 0.147 | See |
| 3 | LogisticRegression | fit | 1.170 | 0.017 | 1000 | 1000 | 10000 | 1.0 | NaN | False | True | 1 | NaN | 100 | auto | NaN | l2 | NaN | lbfgs | 0.0 | 0 | False | [26] | 1.231 | 0.055 | 0.951 | 0.002 | See |
| 4 | LogisticRegression | predict | 0.000 | 0.000 | 1000 | 1 | 10000 | 1.0 | NaN | False | True | 1 | NaN | 100 | auto | NaN | l2 | NaN | lbfgs | 0.0 | 0 | False | NaN | 0.002 | 0.002 | 0.076 | 1.438 | See |
| 5 | LogisticRegression | predict | 0.002 | 0.000 | 1000 | 100 | 10000 | 1.0 | NaN | False | True | 1 | NaN | 100 | auto | NaN | l2 | NaN | lbfgs | 0.0 | 0 | False | NaN | 0.005 | 0.000 | 0.535 | 0.014 | See |
Shared hyperparameters:
| value | |
|---|---|
| penalty | l2 |
| dual | False |
| tol | 0.0001 |
| C | 1.0 |
| fit_intercept | True |
| intercept_scaling | 1 |
| class_weight | NaN |
| random_state | NaN |
| solver | lbfgs |
| max_iter | 100 |
| multi_class | auto |
| verbose | 0 |
| warm_start | False |
| n_jobs | NaN |
| l1_ratio | NaN |
| estimator | function | mean_sklearn | stdev_sklearn | n_samples_train | n_samples | n_features | alpha | copy_X | fit_intercept | max_iter | normalize | random_state | solver | tol | n_iter | mean_daal4py | stdev_daal4py | speedup | stdev_speedup | profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | Ridge | fit | 0.049 | 0.001 | 1000 | 1000 | 1000 | 1.0 | True | True | NaN | False | NaN | auto | 0.001 | NaN | 0.031 | 0.003 | 1.593 | 0.010 | See |
| 1 | Ridge | predict | 0.000 | 0.000 | 1000 | 1 | 1000 | 1.0 | True | True | NaN | False | NaN | auto | 0.001 | NaN | 0.000 | 0.000 | 0.604 | 0.623 | See |
| 2 | Ridge | predict | 0.000 | 0.000 | 1000 | 100 | 1000 | 1.0 | True | True | NaN | False | NaN | auto | 0.001 | NaN | 0.000 | 0.000 | 1.164 | 0.387 | See |
| 3 | Ridge | fit | 0.012 | 0.001 | 10000 | 10000 | 100 | 1.0 | True | True | NaN | False | NaN | auto | 0.001 | NaN | 0.006 | 0.004 | 2.000 | 0.399 | See |
| 4 | Ridge | predict | 0.000 | 0.000 | 10000 | 1 | 100 | 1.0 | True | True | NaN | False | NaN | auto | 0.001 | NaN | 0.000 | 0.000 | 0.668 | 0.609 | See |
| 5 | Ridge | predict | 0.000 | 0.000 | 10000 | 1000 | 100 | 1.0 | True | True | NaN | False | NaN | auto | 0.001 | NaN | 0.000 | 0.000 | 0.620 | 0.298 | See |
Shared hyperparameters:
| value | |
|---|---|
| alpha | 1.0 |
| fit_intercept | True |
| normalize | False |
| copy_X | True |
| max_iter | NaN |
| tol | 0.001 |
| solver | auto |
| random_state | NaN |
{
"system_info": {
"python": "3.8.8 | packaged by conda-forge | (default, Feb 20 2021, 16:22:27) [GCC 9.3.0]",
"executable": "/usr/share/miniconda/envs/sklbench/bin/python",
"machine": "Linux-5.4.0-1046-azure-x86_64-with-glibc2.10"
},
"dependencies_info": {
"pip": "21.1",
"setuptools": "49.6.0.post20210108",
"sklearn": "0.24.1",
"numpy": "1.20.2",
"scipy": "1.6.2",
"Cython": null,
"pandas": "1.2.4",
"matplotlib": null,
"joblib": "1.0.1",
"threadpoolctl": "2.1.0"
},
"threadpool_info": [
{
"filepath": "/usr/share/miniconda/envs/sklbench/lib/libopenblasp-r0.3.12.so",
"prefix": "libopenblas",
"user_api": "blas",
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"version": "0.3.12",
"num_threads": 2,
"threading_layer": "pthreads"
},
{
"filepath": "/usr/share/miniconda/envs/sklbench/lib/libgomp.so.1.0.0",
"prefix": "libgomp",
"user_api": "openmp",
"internal_api": "openmp",
"version": null,
"num_threads": 2
}
],
"cpu_count": 2
}